mirror of https://github.com/open-mmlab/mmocr.git
62 lines
1.9 KiB
Python
62 lines
1.9 KiB
Python
model_poly = dict(
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type='PSENet',
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backbone=dict(
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type='mmdet.ResNet',
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depth=50,
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num_stages=4,
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out_indices=(0, 1, 2, 3),
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frozen_stages=-1,
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norm_cfg=dict(type='SyncBN', requires_grad=True),
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init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50'),
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norm_eval=True,
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style='caffe'),
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neck=dict(
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type='FPNF',
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in_channels=[256, 512, 1024, 2048],
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out_channels=256,
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fusion_type='concat'),
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det_head=dict(
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type='PSEHead',
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in_channels=[256],
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hidden_dim=256,
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out_channel=7,
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module_loss=dict(type='PSEModuleLoss'),
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postprocessor=dict(type='PSEPostprocessor', text_repr_type='poly')),
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data_preprocessor=dict(
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type='TextDetDataPreprocessor',
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mean=[123.675, 116.28, 103.53],
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std=[58.395, 57.12, 57.375],
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bgr_to_rgb=True,
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pad_size_divisor=32))
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model_quad = dict(
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type='PSENet',
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backbone=dict(
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type='mmdet.ResNet',
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depth=50,
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num_stages=4,
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out_indices=(0, 1, 2, 3),
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frozen_stages=-1,
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norm_cfg=dict(type='SyncBN', requires_grad=True),
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norm_eval=True,
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init_cfg=dict(type='Pretrained', checkpoint='torchvision://resnet50'),
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style='pytorch'),
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neck=dict(
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type='FPNF',
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in_channels=[256, 512, 1024, 2048],
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out_channels=256,
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fusion_type='concat'),
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det_head=dict(
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type='PSEHead',
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in_channels=[256],
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hidden_dim=256,
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out_channel=7,
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module_loss=dict(type='PSEModuleLoss'),
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postprocessor=dict(type='PSEPostprocessor', text_repr_type='quad')),
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data_preprocessor=dict(
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type='TextDetDataPreprocessor',
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mean=[123.675, 116.28, 103.53],
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std=[58.395, 57.12, 57.375],
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bgr_to_rgb=True,
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pad_size_divisor=32))
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